In the field of seismic surveying, it is known to conduct repeatedly the same seismic survey several times over a number of years in order to monitor changes to the structure of a reservoir containing hydrocarbons and to identify deformation of the reservoir as a result of hydrocarbon extraction. Such surveys are commonly referred to as time-lapse seismic surveys. One current process for performing time-lapse seismic surveys is simply to undertake several so-called Ocean Bottom Seismic (OBS) node surveys, separated in time in order to find changes between seismic “pictures” generated from data acquired using the OBS surveys.
The trend in OBS data acquisition is towards deploying a large array of sensor nodes on the seabed that operate entirely autonomously, i.e. they are not linked by cable. The sensor nodes are arranged to record four-component seismic signals, by using one hydrophone and three orthogonal geophone sensors, for the duration of the deployment. Typically, these sensor nodes record data at a sampling rate of around 200 to 400 Hz.
In an example of a known deployment, the sensor nodes are placed on the seabed by Remote Operated Vehicles (ROVs), usually in the order of 1000 nodes at any one time. Typically, the sensor nodes are placed in two-dimensional arrays or “patches”, sometimes in a regular arrangement such as a square or a rectangle, and sometimes in more irregular arrangements, and are normally spaced around 400 m to 500 m apart. Once an array of sensor nodes has been deployed, a vessel adapted to perform active seismic transmissions passes over the top of the array many times and discharges a seismic gun repeatedly at around 50 m intervals. The sensor nodes record the resulting seismic data using their hydrophone and geophone sensors to receive the seismic waves generated by the seismic gun and the seismic waves reflected by the various layers of geological structure below the seabed.
The sensor nodes are then recovered by the ROV or a surface vessel and the data downloaded from each sensor node for post-processing.
For effective processing of seismic data, the ability to ensure that sampling instants of every sensor node within the sensor array are “aligned” to a common time frame to a high accuracy, for example approximately ±1 millisecond (ms), is a fundamental requirement so that seismic data between all nodes can be correlated. If time synchronisation is not achieved to this accuracy, the resulting seismic images generated can be degraded and hence inaccurate. In this respect, although measurements are made at the same time, the time noted by each sensor node as to when the measurements were made will not be aligned and so when the seismic images are reproduced by combination of the data collected by each individual sensor node, the misalignment of the measurement times between the sensor nodes will result in distortion of the image.
To this end, time synchronisation within each sensor node is therefore typically achieved with the use of a highly accurate timing module such as an Oven Controlled Crystal Oscillator (OCXO) timing module. Such modules are susceptible to time drift, but can typically keep track of times at which samples are taken (“sample times”) to within an accuracy of a few tens of a millisecond over a 2 to 3 month deployment period before any time drift corrections need to be applied. Each OCXO module is equipped with a battery, typically a rechargeable Lithium Ion (Li-Ion) battery.
Before deployment, the time offset of each sensor node is estimated relative to Coordinated Universal Time (UTC) (or an alternative common time base) using an externally originating Global Navigation Satellite System (GNSS) signal, such as GPS signal, which is provided via a cable connection to each and every sensor node prior to subsea deployment. Thereafter, the sensor nodes are “free running” and therefore subject to timing drift until recovered by the surface vessel or the ROV and again provided with the GNSS signal to measure any final time drifts or offsets.
By measuring the initial and final time offsets with respect to the common time base of each sensor node, analysis of any residual drift of the OCXO timing modules can be performed and corrected, thereby providing a final accuracy of approximately ±1 ms for each sensor node as required for seismic processing.
Having characterised the drift of each OCXO timing module, it is then possible to derive the individual sampling instants of each sensor node and therefore time align the recorded seismic data of all sensor nodes within the entire array as required for seismic post-processing.
However, current nodal OBS systems suffer from a number of drawbacks that restrict the ability to perform seismic surveys accurately. Firstly, the OCXO timing module draws significant power from the battery. This power consumption accounts for a significant portion of the overall power demand of the sensor nodes and therefore typically restricts maximum deployment time to around 2 to 3 months as mentioned above. Secondly, and in any event, the OCXO module component of the sensor node can only maintain synchronisation for 2 to 3 months to the required accuracy of ±1 ms, even after pre-deployment and post-recovery drift measurement and correction has been performed. Therefore, after this time the sensor nodes must be recovered and re-synchronised before they can be used again. Thirdly, in order to maintain time synchronisation, the OCXO timing module must be powered continuously between measurement of initial and final time offsets, otherwise synchronisation is irrevocably lost. Consequently, the sensor node cannot be powered down between seismic measurement events in order to conserve charge of the battery.
The effects of this relatively short-term endurance of the sensor nodes are compounded when there are delays in the deployment or recovery of the sensor nodes and sessions of discharge of the seismic gun, for example: lack of availability of the surface vessel, equipment failure and/or bad weather conditions. Once the life of a sensor node has expired, either due to timing drift and/or depletion of the charge of the battery, the sensor node must be recovered for battery charging and OCXO clock drift measurement, which is a very time consuming and costly exercise.